Since in Bayesian inversion data are often informative only on a low-dimensional subspace of the parameter space,significant computational savings can be achieved using such subspace to characterize and approximate the posterior distribution of the parameters. We study approximations of the posterior covariance matrix defined as low-rank updates...
Creator:
Tenorio, Luis (Colorado School of Mines)
Created:
2017-09-08
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Interbed multiples form a class of multiples in seismic data characterized by the property that all reflection points lie in thesubsurface. This sets them apart from surface multiples, which have at least one reflection point at the surface of the earth.For surface multiples there is a well established procedure to predict them from the data, i....
Creator:
Ten Kroode, Fons (The Shell Group)
Created:
2005-10-20
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
We discuss the role of common knowledge/common information in decision making over networks.We present 'the common knowledge/common information methodology' and show how it can beused to solve a broad class of dynamic team problems that arise in networks and were previouslyunsolved. We demonstrate how the common knowledge methodology can be used...
Creator:
Teneketzis, Demosthenis (University of Michigan)
Created:
2015-09-29
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.